by Anjali Sinha, Dewei Feng, and Justice Vidal
Introduction
With recent advances in quantum computing, more applications for harnessing quantum properties to achieve accelerated computation have come to light. One such developing theoretical field is Quantum Machine Learning. In this article, we will discuss some useful algorithms that enable significant speed-ups with regard to supervised and unsupervised learning.
First, we need to understand why quantum computing offers advantages over other classical approaches. Since qubits, the basic units of quantum computing, interact in accordance with the principles of quantum physics, properties such as quantum entanglement and quantum superposition allow for these systems to process complex data more quickly. …
